In video and image processing, edges of objects in images and video frames may become blurred for many reasons. For example, NTSC analog broadcasts have limited bandwidth, and as a result, the video content is low-pass filtered, which results in smoothing out the high frequency content and thus softening and blurring the edges. Additionally, transmitting analog video over the air tends to add distortions that may result in some blurring. Digital broadcasts such as, for example, MPEG formatted signals are also bandwidth-limited signals which requires compressing the digital content before transmitting over an analog channel, and the compression often results in loss of high frequency content, and effectively blurring and softening of edges. Quantizing high-frequency discrete cosine transform (DCT) basis functions has a similar effect to low-pass filtering. Also, many MPEG systems sub-sample the original 4:4:4 video to 4:2:2 or 4:2:0 and sub-sampling the original video signal also involves low-pass filtering. Blurring may also be the result of hardware limitations such as, for example, not having enough bits of precision in the processor, which may cause loss of information and as a result cause blurriness in addition to other flaws or imperfections in the images.
Often when images' edges get blurred, they get blurred differently, depending on the characteristics of the communication channel over which they are transmitted. Although, the same content may be sent over two separate communications channels, different video outputs may be produced since different channels may behave differently. When broadcasting videos, the luminance/brightness component may be separated from the chrominance/color component, and while they may be sent together, they are processed differently. It is fairly common to have some small amount of mismatch between the two components. Since the human eye is more sensitive to brightness than it is to color, color information is often band-limited or compressed differently than luminance information. Common problems in video and image processing are that the luma edges and chroma edges often do not line up, and the chroma may be a little blurrier or may get phase shifted more than the luma, and as a result, the overall impression of the image may appear softer and blurrier.
Therefore, it is often desirable to enhance the edge of objects in the images or pictures of a video source. There are several applications and variations thereof used for enhancing edges of objects in images and pictures, some of which may include, sharpening luma edges, sharpening chroma edges, and aligning chroma edges to luma edges. The latter may be referred to as chroma transient improvement (CTI). The disadvantage of using CTI is possibly over emphasizing edges, and since CTI operates only in the horizontal direction, there may be a risk of creating perceptible differences between image characteristics in the vertical and horizontal directions.
Sharpening the edges in an image or a picture is intended to give a perception of crispness, or higher contrast. Since video is ultimately perceptual, there are many human factors to consider. Mathematically correct high-pass filters often cause overshoot or ringing artifacts that are perceptually unpleasant and therefore objectionable, and as a result must be prevented.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.